This gets really philosophically deep if you keep going... :)
Like... how do you bootstrap epistemology? Given what you say above, how is it that a completely naive learner learns anything? If you immerse a naive learning entity in random noise, it will only learn random correlations. But if you immerse it in an environment with structure, we must assume it would begin to mirror that structure in its internal state. (Learning is information transfer.) But at some point it has to start somewhere... to start by attempting to correlate one apparently non-random pattern with another.
BTW, I do agree that the graph I posted doesn't prove anything. But if it continues to repeat, at what point should we start questioning the null hypothesis and searching for underlying causal factors? Does statistics have anything to say about that?
This gets into areas like "if we built an autonomous space probe, how would we program it to look for 'interesting' things? Define interesting..."
> Given what you say above, how is it that a completely naive learner learns anything?
Well, that's a very good question, and I think the answer is by being naive, meaning suspending disbelief until the person has enough experience to be an informed consumer of ideas.
> If you immerse a naive learning entity in random noise, it will only learn random correlations.
That's true, but children are natural scientists, naturally curious, predisposed to think there's a mechanism behind everything. If that instinct succeeds, they will look for and sometimes find actual mechanisms -- where they exist.
> But if you immerse it in an environment with structure, we must assume it would begin to mirror that structure in its internal state.
That's true even when the structure is an illusion, as with religion and fixed belief systems. To me personally, the hardest part of growing up is not discovering the real mechanisms of life, but unlearning the phony mechanisms that we tend to be force-fed as children.
> But at some point it has to start somewhere... to start by attempting to correlate one apparently non-random pattern with another.
I would have said that the start is locating a plausible mechanism for a pattern that might otherwise mean nothing, then proving a correlation. Then offering the explanation to one's friends to see if they can find a flaw in your reasoning. Hmm -- I just described about 80% of modern science. :)
> BTW, I do agree that the graph I posted doesn't prove anything. But if it continues to repeat, at what point should we start questioning the null hypothesis and searching for underlying causal factors? Does statistics have anything to say about that?
Yes, it does -- it's the same with all apparently nonrandom sequences. Unless the observer tries to find and test explanations, the default assumption must be that, no matter how persuasive, the data are random and lacking a cause-effect relationship.
Here's my favorite example of what can go wrong. Let's say I'm a doctor and I think I've cured the common cold. My cure is to shake a dried gourd over the patient until he gets better. The cure might take several days but it always works. It's repeatable. It's falsifiable (it might fail, but so far it hasn't). Other laboratories successfully replicate the experiment. So it's "scientific", at least according to the definition of science that doesn't require things to be explained (as with psychology).
To a mature, skeptical mind, everything is wrong with it -- no attempt to explain, confirmation bias, etc. But to someone starting out in life, to someone not sufficiently skeptical, it's a scientific breakthrough. It's not random. :)
Like... how do you bootstrap epistemology? Given what you say above, how is it that a completely naive learner learns anything? If you immerse a naive learning entity in random noise, it will only learn random correlations. But if you immerse it in an environment with structure, we must assume it would begin to mirror that structure in its internal state. (Learning is information transfer.) But at some point it has to start somewhere... to start by attempting to correlate one apparently non-random pattern with another.
BTW, I do agree that the graph I posted doesn't prove anything. But if it continues to repeat, at what point should we start questioning the null hypothesis and searching for underlying causal factors? Does statistics have anything to say about that?
This gets into areas like "if we built an autonomous space probe, how would we program it to look for 'interesting' things? Define interesting..."